Fundamentals of Machine Learning for Healthcare
Completed by Travis Duncan
January 21, 2024
14 hours (approximately)
Travis Duncan's account is verified. Coursera certifies their successful completion of Fundamentals of Machine Learning for Healthcare
What you will learn
Define important relationships between the fields of machine learning, biostatistics, and traditional computer programming.
Learn about advanced neural network architectures for tasks ranging from text classification to object detection and segmentation.
Learn important approaches for leveraging data to train, validate, and test machine learning models.
Understand how dynamic medical practice and discontinuous timelines impact clinical machine learning application development and deployment.
Skills you will gain
- Category: Supervised Learning
- Category: Health Informatics
- Category: Model Evaluation
- Category: Healthcare Industry Knowledge
- Category: Artificial Intelligence and Machine Learning (AI/ML)
- Category: Applied Machine Learning
- Category: Statistical Machine Learning
- Category: Generative Model Architectures
- Category: Machine Learning
- Category: Healthcare Ethics
- Category: Medical Science and Research
- Category: Machine Learning Algorithms
